The present application relates to the in-vivo imaging arts. It finds particular application with workflow and software processing in connection with small animal imaging in a research environment, and will be described with particular reference thereto. It is to be appreciated that the present application also finds use in other clinical and research settings, such as research with human subjects.
Presently available imaging scanners are not equipped with standardized equipment and techniques that support automated and scientifically rigorous workflow suited to the testing of medical hypotheses. Pre-clinical imaging helps to bridge the gap between medical treatment ideas that have not yet been proven reliable and application in human treatment. Pre-clinical animal imaging research can be used to define the conditions and end points for clinical trials. Specifically, pre-clinical in-vivo small animal imaging provides the capability to visualize and quantify metabolic activity, cell proliferation, apoptosis, receptor status and immunoreactions, angiogenesis, and hypoxia, among other relevant biological processes. This is done by indirectly measuring gene expression, enzyme activity, receptors and transporters, and regional concentrations of molecules through a variety of means, most commonly using emission imaging techniques with radio-labeled tracers.
This research is characterized by curiosity and/or by hypothesis driven programs often supported by grants to either discover or explore new insights into biological processes. As such, device characteristics such as sensitivity and spatial resolution are at a premium, particularly when viewed against a continual need to visualize smaller and smaller structures and processes. Additionally, the need for quantification of these processes increases as the research moves from describing systems to measuring systems. This work is primarily conducted in academic medical centers. As such, the knowledge of the community advances through literature, conferences, and symposia. Typically, small scale applications are also pursued for promising research findings. Success criteria include the ability to clearly and effectively demonstrate and expand understanding, whether it results in direct commercial activity or not.
A more specific expression of biological research is the systematic discovery and development of biomarkers, drugs, and therapies that will ultimately be translated from animal models to humans should they prove promising during pre-clinical studies. Distinguishing this area from the more varied general biological area is the need to follow standardized, calibrated processes capable of supporting rigorous regulatory filings. As such, this work is typically (though not exclusively) conducted in commercial pharmaceutical companies and/or instrumentation companies as they seek to discover, develop, and ultimately commercialize drugs and therapies for economic return rather than only build the general knowledge into the processes.
Quantification is important for reliable evaluation of the acquired data. Without the information on tracer concentration in physical, absolute units, different tracers cannot be compared with each other in an objective manner in the context of tracer development. Also, the quality of diagnostic information extracted from the acquired images depends crucially on the quantifiability of the data. Especially from small animal imaging, a variety of considerations such as, for example, partial volume effects play an important role and should be corrected in order to obtain meaningful concentration values. These effects may be mitigated with single-imaging mode design and/or corrections, or through using complementary modality data such as (but not limited to) anatomical information from a CT scan, which can be helpful in this context.
Quantification is valuable in the marketplace. Software tools dealing with partial volume and motion correction, and the like are available, and valuable for reliable quantification. Animal imaging plays an important role in the process of tracer development and validation by reducing the amount of time and effort that has to be spent for evaluating tracer properties. With in-vivo imaging, it is possible to perform a serial analysis of the same animal over a period of time and thus study, for example, the bio-distribution of the tracer over a long time span. Without imaging, the same study would involve many animals, which would have to be sacrificed at various time points to measure the tracer distribution with in-vitro methods. Moreover, by applying such techniques as pharmacokinetic modeling, it is possible to assess multiple biological parameters at once in one imaging procedure.
Pharmacokinetic modeling of pharmacodynamics allows the simultaneous assessment of multiple biological and molecular parameters at once. Since the distribution of the tracer in the animal over the course of time is a dynamic process, static imaging only contains limited information compared to the analysis of dynamic sequences, which provides access to the rate constants governing the kinetic processes.
Pre-clinical applications to support this activity can be summarized as providing users the capability to perform studies of varying scope, each level highlighting requirements or focus areas for the device;
A snapshot measurement on a single subject, e.g., uptake;
Time activity during 1-5 half lives of the radio labeled marker;
A longitudinal study of a single subject across multiple imaging sessions;
A group study with multiple subjects in the same laboratory; and
Population analysis across multiple distributed studies and/or methodologies.
The levels apply most directly to the discovery and development processes for drugs and biomarkers. Software applications implementing these study types is important because doing so facilitates standardization leading to higher quality, more reproducible studies that replace time consuming and error prone manual methods or custom programming that is particularly difficult given the data volume associated with this work. Important standardization should be driven by the instrumentation rather than relying on individual principal investigators.
The present application provides a new and improved small animal handling, imaging, and research data analysis technique that overcomes the above-referenced problems and others.